Online & Offline Experiments Engineer Jobs

1 job found

Today

Lead Machine Learning Engineer

Disney Entertainment and ESPN Product & Technology San Francisco, CA

San Francisco, CA

Today

$188k - $252k/yr Full time Manager Ai Ml Artificial Intelligence

Apply Now

Job Description

Build next-generation personalization for Disney+ and Hulu by leading the ideation, development, iteration, and productionization of recommendation algorithms. This onsite role in San Francisco, CA supports a team that blends applied ML science with end-to-end engineering to improve recommendations using modern AI and LLM techniques, backed by rigorous offline and online evaluation.

What you’ll do

Ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack, including core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
Apply modern AI and LLM techniques to recommendation systems, including generating and improving recommendations, strengthening evaluation, and accelerating model build and improvement cycles.
Shape recommendation approaches by contributing ideas on evaluation methodology and helping define model data, features, and objectives; support other scientists in taking ideas from concept to production.
Drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and influencing how the team approaches them.
Design and run rigorous offline and online experiments, and help improve evaluation systems and methodology over time.
Collaborate closely within the team and across Engineering, Product, and Data, communicating methodologies clearly to both technical and non-technical audiences and managing stakeholder expectations.
Build production-worthy, maintainable systems with strong development, testing, and deployment standards, and provide support when production issues arise.

Core requirements

7+ years of experience developing machine learning models and deploying them to production systems.
Strong background in applied ML science, end-to-end ML engineering, ideally with experience in recommendation systems modeling.
Hands-on experience with AI and LLM techniques and an understanding of the modern AI landscape.
Proficiency with PyTorch, TensorFlow, Databricks, Spark, and SQL.
In-depth understanding of modern machine learning methods, models, and their mathematical foundations.
Strong written and verbal communication skills.
Collaborative, personable working style, thriving across teams rather than operating in isolation.

Bonus and benefits

Bonus and/or long-term incentive units may be provided as part of the compensation package.
Full range of medical, financial, and/or other benefits depending on level and position offered.

Additional qualifications (preferred)

PhD in computer science, statistics, math, or a related quantitative field.
Publications or papers in machine learning or AI, especially in recommender systems.
Production experience developing content recommendation algorithms at scale.
Experience with reinforcement learning or related sequential decision-making approaches.
Experience with recommendation system evaluation methodology, including offline evaluation and A/B experimentation.

Education: BS or MS in Computer Science, Engineering, or a related field.

Salary range: USD 187,900 to 252,000 per year.

Technologies: PyTorch, TensorFlow, Databricks, Spark, SQL, AI, LLM.

View full job page →

Get Online & Offline Experiments Engineer Jobs alerts

New Online & Offline Experiments Engineer Jobs, daily.